Data Engineer

Confidence S. is a Data Engineer with several years of experience in designing and implementing data pipelines and warehouses across various cloud platforms. His core technologies include Python, SQL, and Spark, which he uses to build ELT and ETL pipelines, real-time data ingestion systems, and automated workflows. Confidence is proficient with tools such as Apache Kafka, DBT, and Airflow, and is experienced in managing data warehouses on platforms like BigQuery and AWS Redshift. He ensures robust CI/CD practices using GitHub Actions and Docker. Notable projects include developing a real-time identity fraud detection pipeline using Kafka and PySpark, and leading the migration of enterprise data warehouses to Google BigQuery. He also built a scalable data ingestion platform for LLM training datasets, utilizing AWS S3 and BigQuery. Confidence holds certifications in Google Cloud Professional Data Engineering, Microsoft Fabric Data Engineering, and more. He is well-suited for roles that involve building scalable data solutions and enhancing data quality initiatives in cloud environments.